Robustness optimization for crash safety based on dual-response surface model

Abstract

Robust framework of vehicle body is important to improve the performance of crash safety. Unfortunately, because of neglecting uncertainty variables in manufacturing, material properties and operating conditions, the performance of vehicle crash safety is unstable. In recent years, robust design has been gaining wide attention and applying in automotive industry. The application of dual-response surface method is performed to the robust design of the crashworthiness of a car front rail. In the optimization process, the Latin hypercube sampling (LHS) method and least square method are applied to construct the dual-response surface model, which is second order polynomial response surface, and the scatters of material properties are considered. After the optimization, the robust analysis of the rail is performed. Results show that the dual-response surface method is of high precision, the robustness of front rail crashworthiness is significantly improved, and the weight reduction has reached 3.32% after the robust optimization. © 2011 Journal of Mechanical Engineering.